Improving strategies in stochastic games

J. Flesch*, F. Thuijsman, O.J. J Vrieze

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic


In a zero-sum limiting average stochastic game, we evaluate a\nstrategy π for the maximizing player, player 1, by the reward φ\ns(π) that π guarantees to him when starting in state s.\nA strategy π is called non-improving if\nφs(π)⩾φs(π[h]) for any state s\nand for any finite history h, where π[h] is the strategy π\nconditional on the history h; otherwise the strategy is called\nimproving. We investigate the use of improving and non-improving\nstrategies, and explore the relation between (non-)improvingness and\n(ε-) optimality. Improving strategies appear to play a very\nimportant role for obtaining ε optimality, while 0-optimal\nstrategies are always non-improving. Several examples are given to\nclarify all these issues
Original languageEnglish
Title of host publicationProceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171)
Number of pages6
Publication statusPublished - 1998

Publication series

SeriesProceedings of the IEEE Conference on Decision and Control

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